Why these three
Read from the founder's seat after a $160M raise at $1B, the priorities are clear: scale to demand without breaking the one-day promise, defend the pharma revenue that prices the Series C, and lift first-pass approvals so prevention replaces appeals. Each gets a working tool below, and each tool carries a one-page brief inside it: what it shows, what production looks like, and the experience behind it.
The prototypes
Prototype 01 · Ops & growth
The capacity crystal ball
The question it answers: will ops break at 10x, in which month, and is the fix hiring or automation?
- 18-month forecast: PA volume → reviewer utilization → time-to-therapy, with the break-month as one number
- Automation backlog stack-ranked by reviewer headcount offset at months 4, 8, and 12 (the math exposed)
- Build-vs-hire priced in one currency: reviewer-equivalents
Open the simulator →forus.jeffpinto.com/capacity
Prototype 02 · Revenue & renewals
The renewal defense
The question it answers: can the lift claims survive the client's own analysts and Series C diligence?
- A brand-impact report in the client's units, selection-bias objection answered before it's raised
- Within-provider difference-in-differences, adoption event study, payer-filterable funnel
- One honest null, by design: credibility that compounds across a contract
Open the report →forus.jeffpinto.com/proof
Prototype 03 · Product & AI
The first-pass approval machine
The question it answers: which submissions will bounce, why, and where does one reviewer-hour buy the most approvals?
- A triage queue ranked by calibrated denial probability, each case carrying its driver and a concrete fix
- Model quality in CEO units: first-pass lift, appeal-hours avoided, patient-days saved
- A model card that takes label hygiene, payer-rule drift, and the feedback loop seriously
Open the console →forus.jeffpinto.com/approvals
The same person shows up in all three
This seat asks for an unusual combination: analytical depth, ops instinct, and client presence. The prototypes are the argument; here's the history behind them.
Scale & forecastingLed product analytics for the Uber Market launch (courier supply and throughput under hypergrowth). Ecosystem lead for Meta AI on Ray-Ban smart glasses: growth, forecasting, experimentation.
Client-facing measurementDirector of Solutions closing & implementing $1.5M/yr in SaaS, presenting numbers to paying clients and their analysts. Defined launch success metrics across Meta and Uber.
Clinical NLP & health AIML/NLP researcher at CAMH: extracting symptoms, side effects & medications from scanned clinical notes (Forus's core substrate). CIO & Head of AI at Blue Mesa Health (acquired by Virgin Pulse). MSc Computational Linguistics, University of Toronto.
Team & trust at scaleSenior DS at Meta leading a 10-person analytics team; privacy infrastructure for LLM training data. High-stakes, regulator-visible work. 2x Clear Vision award; invention disclosure for AI-enabled alerts via Meta's patent program.
CV at a glance
2020-nowMeta: Senior Data ScientistPrivacy infra for LLM training data · led 10-person creator-ads analytics team · Meta AI on smart glasses · shipped IG auto-captions
2019-20Uber: Senior Product Analyst / Team LeadLaunch analytics for Uber Market · led team of 8 across Uber's consumer financial products
2019Blue Mesa Health: CIO & Head of AIConversational AI for chronic-disease coaching · 12-person eng & support org · acquired by Virgin Pulse
2017-18CAMH: ML/NLP ResearcherAutomated extraction of symptoms, side effects & medications from scanned psychiatric notes
2009-15Sparkroom: Director of SolutionsClosed & implemented $1.5M/yr net new SaaS · authored client discovery playbook
MSc Computational Linguistics (U of Toronto, clinical-NLP capstone) · MSc Renewable Energy w/ Distinction (Loughborough) · 2x Meta Clear Vision award · CLEF eHealth multilingual ICD-10 classification (2018)
The prototypes are the interview.
Synthetic data throughout; independent concept work, not affiliated with Forus. If any of these is worth a real conversation, I'd love to have it.